Self-optimised search and navigation

Move from manual, labour-intense search and category merchandising toward a completely programmatic solution. No drag and drop interface, no manual rule setting, once live with Loop54 everything is automated.

Search and category merchandising

Learning new words

Words that do not exist in the catalogue are learnt and assigned as synonyms. This includes misspelled words that lead to conversions.

Interpreting behaviour data

Without compromising performance, behaviour data is processed in real-time in order to define customer segments and provide a more personalised experience.

Understanding search intent

The algorithm locates and maps complex product relationships. This allows it to generate a list of Related Results that do not contain the search query in their metadata but are relevant nonetheless.

How we automate

Loop54 is a Machine Learning search algorithm accessible via an API and hosted in the cloud. It is not a toolbox for manually creating custom keyword tags, variant labels, synonym lists or boost and bury rules. That's done automatically!

At setup, business rules are built into the algorithm logic - such as detecting new items, campaigns, stockouts, etc.

Behaviour data is continuously added to the algorithm logic; products re-sort for greater relevance and personalisation

Real-time learning capabilities are used to incorporate new words and synonyms into algorithm logic

“After careful evaluation, Loop54 was the obvious choice for us. We were tired of the performance issues and maintenance of Lucene and ElasticSearch. Loop54 gave us the automation, relevance and stability we demanded. Now our conversion rate from search is up 30%!”

Erik Nielsen, Web and E-Commerce Manager at Teknikmagasinet

“Just one month after implementing Loop54 we were please to see engagement with search results jump to 80%. Not only that, our engine learned 500 new search terms and attached 14500 click, add-to-cart and purchase events to both search queries and unique users - giving us tremendous insight into customer behaviour we never had before.”

Catarina Tagebjer, E-commerce Manager at Svenskt Tenn

Why we automate

Machine Learning can optimise many eCommerce systems. But due to its complexity, we believe product search and navigation will gain most from a self-optised algorithm that anticipates shopper intent and minimises operational expenditures.

Succeed like so many others

68%

Incresed revenue from search visits

70%

Reduced search exit

12%

Increased online revenues

Get started

Using our customers as examples, we'll demonstrate how we improve search relevance and personalisation, and automate all search merchandising work.